Modeling and optimal energy operation considering probabilistic and sustainable renewable energy models and demand side management

While the economic is rapidly developing, human beings are facing a serious ecological problems, sustainable-development has got attention from more and more countries and has been treated as an economic and social development strategy. The development and utilization of renewable energy can realize the transformation of regional economic development mode and promote the long-term sustainable development of regional economy. One of the latest concepts that has attracted a lot of attention in the power systems is the energy hub (EH). In this paper, a combined energy system (CES) known as the EH consisting of electrical, cooling and heating equipment along with the demand response programs (DRPs) as well as renewable energy resources (RERs) optimization study have been proposed. Moreover, the uncertainty modeling and electrical scenario creation of cooling, heating, wind speed, solar irradiation and the energy carriers prices including electricity and natural gas is presented. The objective of the optimization problem is maximizing the profit of the EH with the existence of DRPs and RERs under four scenarios which is solved by enhanced grey wolf optimization (GWO) algorithm. In order to avoid such deficiencies and to realize a stabilized relationship between exploration and exploitation, a new modified grey wolf optimization (MGWO) algorithm is proposed. The implementation results show high accuracy and power levels of this method to solve the aforementioned problem under different uncertain parameters and various scenarios. The simulation results of proposed EH profit maximization model shows a reduction in purchased electricity from the main grid and a reduction of the overall operation costs. (C) 2020 Published by Elsevier B.V.